Value of information of combinations of proof loading and pore pressure monitoring for flood defences

Krogt, Mark G. van der; Klerk, Wouter Jan; Kanning, W.; Schweckendiek, T.; Kok, Matthijs

doi:10.1080/15732479.2020.1857794

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…The applications of VOI on flood mitigation include the quantification of benefits of forecasting for flood warnings (Verkade & Werner, 2011), the design of stage monitoring systems (Alfonso & Price, 2012), the monitoring of flood dikes to improve breaching models (Schweckendiek & Vrouwenvelder, 2015;van der Krogt et al, 2022), optimal dike investments under uncertainty (Thorne et al, 2015;van der Pol et al, 2014), and the value of probabilistic flood maps to support decisionmaking (Alfonso et al, 2016). Although the application themes are varied, the term "VOI" is mostly used loosely in FRM literature, not following the technical definition presented in this article: the value a decision-maker is willing to pay for extra information before deciding.…”

Section: Voi Use In Frmmentioning

confidence: 99%

“…They are all based on a Bayesian statistical framework; hence, uncertainty must be modeled through probability theory. The key concept in calculating VOI is updating a prior belief about plausible values for a parameter with the support for likely values of that parameter drawn from additional information, also referred to as Bayesian pre-posterior analysis (van der Krogt et al, 2022). Among the VOI variants, the expected value of perfect information (EVPI) and the expected value of perfect partial information (EVPPI) are two of the most used in healthcare economics, and are used in this article.…”

Section: Voi Estimationmentioning

confidence: 99%

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Not all sources of uncertainty are worth resolving: A value of information approach for uncertainty reduction in flood risk management

Velandia,

Alfonso

2024

J Flood Risk Management

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Flood risk management faces challenging decisions to balance between reducing disastrous flood consequences and different societal goals such as development. The inherent complexity and limited data often lead to significant uncertainties in decision‐making, potentially resulting in suboptimal resource allocation. Consequently, there may be value in aiming to reduce uncertainty, minimizing the possibility of selecting deemed efficient decisions because of deficiencies in the current knowledge. To address this, a novel methodology is proposed, integrating Bayesian uncertainty with value of information concepts, commonly employed in healthcare economics. This methodology assesses the implications of current uncertainty and identifies worthwhile sources for resolution prior making decisions. Validation in a synthetic case study and application in a real case (Zapayan wetland in the Magdalena River, Colombia) demonstrate the method's efficacy. Results show that the proposed method can help apprising if the available information is enough to make a decision, or if more information should be obtained. For example, for the synthetic case, resolving the sources of uncertainty with extra information does not significantly improve the expected utility, so a decision could be made based on existing information. For the real case, reducing the uncertainty related to the exposed assets should be targeted first, by an information gathering activity, before deciding.

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Section: Voi Use In Frmmentioning

confidence: 99%

Section: Voi Estimationmentioning

confidence: 99%

Not all sources of uncertainty are worth resolving: A value of information approach for uncertainty reduction in flood risk management

Velandia,

Alfonso

2024

J Flood Risk Management

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“…The slope instability project developed a step-by-step plan for the detailed modelling of the strength of a flood defence. This involved using specific soil investigation and monitoring and advanced calculation techniques, including probabilistic failure probability analyses and failure probability updating, to estimate the actual current strength for the slope-instability failure mechanism as closely as possible [33][34][35][36][37]. Applying the step-by-step plan reduced the need for reinforcement on many projects, and at some locations, reinforcement proved to no longer be necessary.…”

Section: Monitoring Knowledge and Innovationmentioning

confidence: 99%

The Dutch Flood Protection Programme: Taking Innovations to the Next Level

Tromp

Nijenhuis²,

Knoeff

2022

Water

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The Dutch regional water authorities face an enormous task: the strengthening of about 1500 km of dikes and 500 civil-engineering structures before 2050. This immense operation is being funded, prioritised and supported by the Dutch Flood Protection Programme (DFPP), an alliance of regional water authorities and the Ministry of Infrastructure and Water Management. The work will be executed in nearly 300 projects located throughout the country on the coast, lakes and major rivers. To complete this task on time and within budget, innovation (a better insight into the behaviour of flood defences, new techniques and processes) is believed to be the way forward. In this paper, we look at how the DFPP has encouraged innovations between 2012 and the present. We stress the importance of using a sender–receiver approach to further knowledge transfer and uptake, and we describe how, by using an action research approach, the Dutch Flood Protection Programme is currently adapting its innovation strategy on the basis of lessons learned to improve knowledge uptake. We will address some of the innovations that have been developed over the years and how monitoring knowledge uptake helps to further improve the learning-by-doing approach.

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“…Examples are assessments using physics-based system performance models, such as those found in structural reliability applications [13,31]. In this context, the value of information concept is applied mainly for optimization of inspection and monitoring schemes [e.g., 32,33,34,35,36,37,38]. Rather surprisingly, its use as a sensitivity metric has received little attention.…”

Section: Introductionmentioning

confidence: 99%

Decision-theoretic reliability sensitivity

Straub¹,

Ehre²,

Papaioannou³

2021

Preprint

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We propose and discuss sensitivity metrics for reliability analysis, which are based on the value of information. These metrics are easier to interpret than other existing sensitivity metrics in the context of a specific decision and they are applicable to any type of reliability assessment, including those with dependent inputs. We develop computational strategies that enable efficient evaluation of these metrics, in some scenarios without additional runs of the deterministic model. The metrics are investigated by application to numerical examples.

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Value of information of combinations of proof loading and pore pressure monitoring for flood defences

Cited by 6 publications

References 28 publications

Not all sources of uncertainty are worth resolving: A value of information approach for uncertainty reduction in flood risk management

Not all sources of uncertainty are worth resolving: A value of information approach for uncertainty reduction in flood risk management

The Dutch Flood Protection Programme: Taking Innovations to the Next Level

Decision-theoretic reliability sensitivity

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